This paper presents a COMP, demonstrating the power and potential of dose-surface maps to investigate spatial effects of treatment planning parameters on delivered dose to the rectum.
This paper presents a novel methodology to distinguish between metastatic and healthy bone lesions using lesion-center-based geometric regions of interest, radiomics, and machine learning.
This paper describes the pan-Canadian efforts of the Canadian Partnership for Quality Radiotherapy to champion the use of patient-reported outcomes in Canadian radiation oncology practice.
This paper examines the relative biological effectiveness of DNA damage generated by thermal neutrons compared to gamma radiation. It uses experimental data gathered using the 64 meV neutron beam at the National Research Universal reactor at Canadian Nuclear Labs.
This paper describes a protocol to develop a mobile health app prototype for coordinating respite care services for families coping with palliative-stage cancer in Quebec.
This paper, we describe an effort that began as an undergraduate term-research project of Hui Wang to semi-automate the process of categorizing incident reports in radiation oncology using natural language processing.
This paper, which describes a method to extract physician-reported pain from clinical notes, is the outcome of the first part of the PhD project of student Hossein Naseri. Hossein's is developing an NLP and radiomics pipeline to predict pain in patients with bone metastases in order to potentially enable prophylactic palliative radiotherapy treatments.
This paper, which is the culmination of Logan Montgomery's PhD studies, describes Logan's work simulating the direct action of ionizing radiation on a geometrical model of human DNA using the TOPAS-nBio framework. It builds upon our previous NICE research, in particular the MSc project of Chris Lund.